在医学中使用大型语言模型:谨慎行事
Jiawen Deng1, Areeba Zubair1, Ye-Jean Park1
1Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Current medical research and opinion
|December 14, 2023
概括
大型语言模型具有临床潜力,但面临诸如不准确性和伦理问题等采用障碍. 谨慎,乐观的方法对于安全融入医疗保健至关重要.
科学领域:
- 人工智能在医学中的应用
- 临床信息学 临床信息学
背景情况:
- 大型语言模型 (LLM) 展示了临床应用的潜力,利用对话能力和医学知识编码.
- 像ChatGPT和Bard这样的当前法学士学位显示出希望,但需要对医疗保健机构进行仔细评估.
研究的目的:
- 探索大型语言模型的潜在临床应用.
- 确定阻碍在医疗保健中采用LLM的挑战和伦理考虑.
- 提出一个平衡的方法,将LLMs纳入临床实践.
主要方法:
- 审查与医学知识相关的当前大型语言模型能力.
- 分析记录的局限性,包括模型"幻觉",缺乏透明度和不一致性.
- 审查伦理和法律问题:患者同意,责任和数据隐私.
主要成果:
- 虽然LLM具有临床任务的能力,但也面临着重大挑战.
- 关键障碍包括技术限制 (幻觉,一致性) 和道德/法律问题 (隐私,同意,责任).
结论:
- 在临床环境中,LLM很有前途,但需要严格的验证.
- 谨慎而乐观的战略对于负责任的LLM整合到医疗保健中至关重要.
- 解决技术和道德方面的挑战对于安全有效的临床使用至关重要.
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